Title
Long Memory Modeling and Forecasting: Evidence from the U.S. Historical Series of Inflation
Document Type
Article
Publication Date
2020
Publication Title
Studies in Nonlinear Dynamics and Econometrics
Abstract
We report the results of applying several long-memory models to the historical monthly U.S.inflation rate series and analyze their out-of-sample forecasting performance over different horizons. We findthat the time-varying approach to estimating inflation persistence outperforms the models that assume aconstant long-memory process. In addition, we examine the link between inflation persistence and exchangerate regimes. Our results support the hypothesis that floating exchange rates associate with increased inflationpersistence. This finding, however, is less pronounced during the era of the Great Moderation and the FederalReserve System’s commitment to inflation targeting.
Keywords
Long memory; Time-varying persistence; U.S. inflation; Wavelet analysis
Disciplines
Economics
Language
English
Rights
IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/
Repository Citation
Boubaker, H.,
Canarella, G.,
Gupta, R.,
Miller, S. M.
(2020).
Long Memory Modeling and Forecasting: Evidence from the U.S. Historical Series of Inflation.
Studies in Nonlinear Dynamics and Econometrics
http://dx.doi.org/10.1515/snde-2018-0116